Evaluation and development of sustainable urban land use plans through spatial optimization

Along with rapid global urbanization, cities are challenged by environmental risks and resource scarcity. Sustainable urban planning is central to address the dilemma of economic growth and ecosystem protection, where the use of land is critical. Sustainable land use patterns are spatially explicit in nature, and can be structured and addressed using spatial optimization integrating GIS and mathematical models. This research discusses prominent sustainability concerns in land use planning and suggests a generalized multi‐objective spatial optimization model to facilitate conventional planning. The model is structured to meet land use demand while satisfying the requirements of the physical environment, society and economy. Unlike existing work relying on raster data, due to its simple data structure and ease of spatial relationship evaluation, this research develops an approach for identifying land use solutions based on vector data that better reflects the actual shape and spatial layout of land parcels as well as the ways land use information is managed in practice. An evolutionary algorithm is developed to find the set of efficient (Pareto) solutions given the complexity of vector‐based representations of space. The proposed approach is applied in an empirical study of Dafeng, China in order to support local urban growth and development. The results demonstrate that spatial optimization can be a powerful tool for deriving effective and efficient land use planning strategies. A comparison to results using a raster data approach supports the superiority of land use optimization using vector data as part of planning practice.     

基于地形梯度的山地流域土地利用格局及时空演变研究——以云南小江流域为例

地形差异是山区土地利用结构和空间格局分异的重要影响因素,云南小江流域作为典型山地流域的代表,针对其土地利用结构不合理导致生态环境恶化的问题,文中提出利用小江流域1990、2000、2010年三期土地利用数据,采用GIS空间分析技术,在简要分析土地利用宏观总体格局及变化的基础上,分析流域4大垂直带谱的土地利用格局,并分析驱动因素。重点从高程和坡度两个因子分析流域土地利用格局及演变的地形梯度特征,得出土地利用变化所在的各地形梯度位置范围,可为小江流域土地利用结构优化、土地资源合理利用和生态环境治理及改善提供重要参考。     

Incorporating sprawl and adjacency measures in land‐use forecasting model: A case study of Collin County,TX

Sprawl measures have largely been neglected in land‐use forecasting models. The current approach for land‐use allocation using optimization mostly utilizes objective functions and constraints that are non‐spatial in nature. Application of spatial constraints could take care of the contiguity and compactness of land uses and can be utilized to address urban sprawl. Because a land‐use model is used as an input to transportation modeling, a better spatial allocation strategy for more compact land‐use projections will promote better transportation planning and sustainable development. This study formulates a scenario‐based approach to normative modeling of urban sprawl. In doing so, it seeks to improve the land‐use projections by employing a spatial optimization model with contiguity and compactness consideration. This study incorporates urban sprawl measures based on smart growth principles together with a mixed‐use factor, and adjacency consideration of nearby land uses. The objective function used in the study maximizes net suitability based on imposed constraints. These constraints are based on smart growth principles that enhance walkability in neighborhoods, promote better health for residents, and encourage mixed‐use development. The formulated model has been applied to Collin County, TX, a fast‐developing suburban county located to the north of the Dallas–Fort Worth metroplex. The suitability of land cells indicates the probability of conversion, which is calculated using spatial discrete choice analysis with Moran eigenvector spatial filtering for vacant cells at a resolution of 150 × 150 m employing factors of the built environment, and socioeconomic and demographic characteristics. This study demonstrates how spatial proximity between land uses, which has been ignored to date, can be used to control sprawl, resulting in better mixing of different land uses based on constraints imposed in a spatial optimization problem.     

Optimization of land use structure based on ecological GREEN equivalent

Optimization of land use structure consists of economic and social and ecological optimization. Applying the minds of system engineering and principles of ecology, this paper presents such thoughts: the optimal forest-coverage rate calculated according to the reality of a district is set as main standard of ecological rationality in the district; through considering the value of ecosystem services of the land with GREEN equivalent (mainly cultivated land and grassland) and based on the rule, GREEN equivalent, this paper introduces the area conversion between woodland and cultivated land, also between woodland and grassland; this paper establishes a multi-dimension controlling model of optimization of land use structure. In addition, a multi-objective linear programming model for optimization of land use structure is designed. In the end, this paper tests and verifies this theory of ecological optimization, taking Qionghai city in Hainan Province as an example.     

Optimization of Land Use Structure Based on Ecological GREEN Equivalent

Optimization of land use structure consists of economic and social and ecological optimization.Applying the minds of system engineering and principles of ecology,this paper presents such thoughts:the optimal forest-coverage rate calculated according to the reality of a district is set as main standard of ecological rationality in the district;through considering the value of ecosystem services of the land with GREEN equivalent(mainly cultivated land and grassland)and based on the rule GREEN equivalent,this paper introduces the area conversion between woodland and cultivated land ,also between woodland and grassland;this paper establishes a multi-dimension controlling model of optimization of land use structure,In addition,a multiobjective linear programming model for optimization of land use structure is designed.In the end,this paper tests and verifies this theory of ecological optimization,taking Qionghai city in Hainan Province as an example.     

基于CLUE-S模型和生态安全格局的石羊河流域土地利用优化配置

以典型干旱内陆河流域石羊河为例,将GIS技术、最小累积阻力（minimum cumulative resistance,MCR）模型和CLUE-S（conversion of land use and its effects at small regional extent）模型应用到该流域土地利用优化配置研究中。通过景观安全格局理论构建土地利用生态安全格局,基于土地利用空间分布和驱动因子的定量关系,提出一种基于生态安全格局的土地利用情景模拟方法,借助1986年、2000年和2014年3期土地利用数据对石羊河流域生态安全格局情景、耕地保护情景和自然发展情景3种模式下2030年的土地利用结构和布局进行了优化配置,并对优化配置结果进行比较分析。结果表明,在生态安全情景下耕地有所减少,林地、草地和水域有较明显增加;耕地保护情景以土地开发和整治及宅基地还耕为主要目标,科学有效控制了建设用地规模,大力开发未利用地潜力;自然发展情景综合考虑了目前发展情况和宏观政策指导下各土地利用类型的数量及空间结构发展情况。综合考虑石羊河流域社会经济、生态及耕地保护等多方面的因素,研究结果认为耕地保护情景更为合理,其它两种情景可为耕地保护情景进行补充和局部修正。该结果可为石羊河流域土地利用总体规划和生态保护提供参考。     

Tourism land use simulation for regional tourism planning using POIs and cellular automata

Previous studies on tourism land use primarily focus on the spatial distribution, and its related impacts on the environment. Here, we propose a future tourism land use simulation model for mountain vacations based on the cellular automata and Markov chain methods, having verified and simulated tourism land use in Emeishan city at a spatial resolution of 30 × 30 m using remote sensing and GIS. In addition, we introduced a tourism land use intensity index to study the spatial expansion mode of tourism land use. The results have confirmed the validity of the model and demonstrated its ability to simulate future tourism land use. The average growth rate of tourism land use from 2010 to 2015 is 33.36%, and tourism land use will rise from 1.26% of Emeishan city’s land area in 2015 to 2.95% in 2030. Tourism land use shows a spatial expansion pattern along channels from scenic spots to the urban area. The growth of tourism land use in the protected area has an increasing trend when there is no restriction on development, especially in the Eshan region. The simulation results can provide useful implications and guides for regional tourism planning and management.     

基于遗传算法的土地利用结构优化研究

以海南省琼海市土地利用结构优化为例，对遗传算法在土地利用结构优化模型中的运用进行了较为系统的分析和探讨，构建出一套土地利用结构优化的多目标线性规划模型，并运用多目标的Pareto方法成功地对模型进行了解算，为今后的土地利用规划工作提供有益的参考。     

城市用地空间信息分类与数字重建——以长春百年城市内部用地变化为例

针对单一应用遥感影像难以进行城市内部用地结构分类以及高精度城市内部用地多期空间数据叠置分析中位置误差问题建立了基于"分层分类"与"对象分割"的城市内部用地空间信息数字重建方法。实现对特大城市产业用地(住宅、商业、工业等)以及交通、水系、生态绿地等不同功能结构用地的高精度监测以及历史演变过程的重建。综合集成SPOT5,1︰1万地形图、历史地图及城市规划图等辅助信息对长春城市1905年以来城市用地信息进行分类。研究表明,在专家知识参与下人—机交互解译,集成多源空间信息对实现高精度城市用地空间信息重建具有较高的应用价值,该方法不仅能提高城市用地分类精度而且能提高城市用地空间信息提取效率以及多期空间数据叠置分析的定位精度。     

国土综合整治三维模型碎片加载优化与调度

国土整治作为一项国家战略,是解决社会经济发展过程中土地利用问题的重要手段,能有效促进国土空间优化和治理土地退化,对于实施乡村振兴战略和推进生态文明建设具有重大意义。随着我国工业化、城镇化的推进,生产、生活、生态之间矛盾日益凸显,国土整治在全国各地广泛开展,尤其是三维可视化技术的应用发展迅速。但对于国土整治业务而言,三维模型存在数据量大、数据复杂且碎片化程度高等特点,使得三维数据的存储管理和加载调度难度大,制约了其在国土整治中的应用。本文针对国土整治三维数据,提出了存储结构优化方法、三维模型碎片加载优化方法和三维模型调度优化方法,并开展了试验验证和应用示范,验证了本文提出的方法能够有效支撑国土整治中的三维可视化相关业务。     

面向服务的国土资源空间数据集成与共享

国土资源海量空间数据的集成与共享一直是国土资源信息化建设中的重要难点问题之一。SOA技术的发展及其在GIS中的应用,为地理空间数据的集成与共享提供了新的技术手段,本文从国土资源空间数据集成与共享的应用需求出发,对基于SOA的国土资源空间数据集成与共享的分层结构进行了分析,同时,对国土资源空间数据的多级集成及共享进行了探讨。     

在Unix与Oracle环境下ArcSDE的优化

第二次全国土地调查成果验收完入库后,为了更好地管理、利用和共享这些土地资源数据,本文提出一套优化存储管理土地数据的方案,分别就服务器端的Unix操作系统、Oracle数据库管理系统以及中间件空间数据引擎ArcSDE提供了一些性能优化的方法。     

Development of a GIS-based decision support system for assessing land use status

The objectives of this study are to assess land suitability and to predict the spatial and temporal changes in land use types (LUTs) by using GIS-based land use management decision support system. A GIS database with data on climate, topography, soil characteristic, irrigation condition, fertilizer application, and special socioeconomic activities has been developed and used for the evaluation of land productivity for different crops by integrating with a crop growth model—the erosion productivity impact calculator (EPIC). International food policy simulation model (IFPSIM) is also embedded into GIS for the predictions of how crop demands and crop market prices will change under alternative policy scenarios. An inference engine (IE) including land use choice model is developed to illustrate land use choice behavior based on logit models, which allows to analyze how diversified factors ranging from climate changes, crop price changes to land management changes can effect the distribution of agricultural land use. A test for integrated simulation is taken in each 0.1o by 0.1o grid cell to predict the change of agricultural land use types at global level. Global land use changes are simulated from 1992 to 2050.     

基于FLUS模型的土地利用变化模拟与预测方法研究

模拟和预测土地利用演变过程是规划者把握城市扩张趋势,从而确定更合理的城市用地布局的重要途径之一,对指导国土空间规划具有重要意义.研究基于CA原理改进的FLUS模型,通过耦合GeoSOS-FLUS及ArcGIS软件,从2011年土地利用数据中获取元胞转换概率,模拟了2018年土地利用变化情况.模拟精度较高,证明选取的模拟...     

GIS应用数据库设计二阶分析模式

提出了数据库设计二阶分析模式，将二者分别应用于空间数据建模和数据库结构设计中，并以国土资源与房地产管理综合管理系统数据库设计中房地关联部分为例对二阶分析模式的应用进行了说明，对模式的可行性进行了论证。     

Development of a GIS-based decision support system for assessing land use status

IntroductionAgriculturallandusepatternsandtheirchangesaretightlyrelatedwithagriculturepolicyandfoodsecurityissuesundergrowingfooddemand,assess mentofglobalclimatechangeimpactsonagricul ture,environmentalissuesduetotheintensificationofagriculturallandusessuchaswaterpollution,soildegradation,andrecentlywaterscarcityissues.Soasustainableandholisticplanningandmanage mentoflandresourcesshouldcombineallthesere latedinformationwithefficienttoolsforassessmentandevaluationinordertopermitbroad ,interact…     

LAND USE SCANNER: An integrated GIS based model for long term projections of land use in urban and rural areas

This paper describes the structure of the LAND USE SCANNER model, a GIS based model developed to generate spatial forecasts for various types of land use for a large number of grids. The model basically allocates land according to bid prices for various types of land use. The possibility of government intervention in land use is taken into account among others by adding aggregate constraints. The model includes all relevant land use types such as residential, industrial, agricultural, natural areas and water. The model is driven by sectoral models providing forecasts of aggregate land use in various land use categories. An application of the first version of the model is given for the Netherlands with some 200,000 grid cells. Further developments and refinements of the model are planned for the near future. Received: 18 February 1998/Accepted: 29 September 1998     

多源空间信息集成技术在铁路用地信息管理中的应用

铁路信息化和数据标准化对铁路用地信息管理提出了更高的要求,多源空间信息集成技术是集成各种铁路空间数据、实现铁路用地信息化管理的基础。本文根据铁路用地空间数据的来源和组成,针对数据的多源、多尺度、动态等特点,提出了基于元数据驱动的铁路用地空间数据集成技术框架,设计了三层分布式C/S铁路用地信息系统结构,所构建的"武汉铁路局铁路用地综合信息管理系统"已取得理想的实际应用效果。     

Spatio‐temporal land use multi‐objective optimization: A case study in Central China

Much effort has been applied to the study of land use multi‐objective optimization. However, most of these studies have focused on the final land use scenarios in the projected year, without considering how to reach the final optimized land use scenario. To fill this gap, a spatio‐temporal land use multi‐objective optimization (STLU‐MOO) model is innovatively proposed in this research to determine possible spatial land use solutions over time. The STLU‐MOO is an extension of a genetic land use multi‐objective optimization model (LU‐MOO) in which the LU‐MOO is generally carried out in different years, and the solutions at year T will affect the solutions at year T + 1. We used the Wuhan agglomeration (WHA) as our case study area. The STLU‐MOO model was employed separately for the nine cities in the WHA, and social, economic, and environmental objectives have been considered. The success of the experiments in the case study demonstrated the value and novelty of our proposed STLU‐MOO model. In addition, the results also indicated that the objectives considered in the case study were in conflict. According to the results, the optimal land use plan in 2050 can be traced back to 2040, 2030, and 2020, providing a series of Pareto solutions over the years which can provide spatio‐temporal land use multi‐objective optimization solutions to support the land use planning process.     

Regional land-use allocation using a coupled MAS and GA model: from local simulation to global optimization,a case study in Caidian District,Wuhan, China

China is facing the pressures of both rapid economic development and environmental protection, and land-use allocation optimization is an important way to manage the conflicts between these pressures and to achieve sustainable development. Optimization of land-use allocation is a nonlinear multiobjective spatial optimization problem, and a purely local simulation model or global optimization model is insufficient to solve it. It is essential to bridge the gap between the two models through the combination of top-down and bottom-up approaches. This study integrates a multiagent system (MAS) that simulates the behaviors of land-use stakeholders with regard to their choices of specific locations, with a genetic algorithm (GA) that simultaneously evaluates and optimizes land-use configurations to meet various regional development objectives. The model is expected to achieve the optimization of land use in terms of the composition and spatial configuration. Caidian District, Wuhan, China, was chosen as the study area to test the model in this paper. The results show that the performance of the coupled model is superior to a pure GA model or MAS model. The optimal configuration improves on the economic output, spatial compactness, and carbon storage of the current configuration and promotes sustainable regional land-use development from the local scale to the regional scale.